DNA mismatch and damage patterns revealed by single-molecule sequencing.

Mutations accumulate in the genome of every cell of the body throughout life, causing cancer and other diseases1,2. Most mutations begin as nucleotide mismatches or damage in one of the two strands of the DNA before becoming double-strand mutations if unrepaired or misrepaired3,4. However, current DNA-sequencing technologies cannot accurately resolve these initial single-strand events. Here we develop a single-molecule, long-read sequencing method (Hairpin Duplex Enhanced Fidelity sequencing (HiDEF-seq)) that achieves single-molecule fidelity for base substitutions when present in either one or both DNA strands. HiDEF-seq also detects cytosine deamination-a common type of DNA damage-with single-molecule fidelity. We profiled 134 samples from diverse tissues, including from individuals with cancer predisposition syndromes, and derive from them single-strand mismatch and damage signatures. We find correspondences between these single-strand signatures and known double-strand mutational signatures, which resolves the identity of the initiating lesions. Tumours deficient in both mismatch repair and replicative polymerase proofreading show distinct single-strand mismatch patterns compared to samples that are deficient in only polymerase proofreading. We also define a single-strand damage signature for APOBEC3A. In the mitochondrial genome, our findings support a mutagenic mechanism occurring primarily during replication. As double-strand DNA mutations are only the end point of the mutation process, our approach to detect the initiating single-strand events at single-molecule resolution will enable studies of how mutations arise in a variety of contexts, especially in cancer and ageing.

Ultra-Rapid Droplet Digital PCR Enables Intraoperative Tumor Quantification.

The diagnosis and treatment of tumors often depends on molecular-genetic data. However, rapid and iterative access to molecular data is not currently feasible during surgery, complicating intraoperative diagnosis and precluding measurement of tumor cell burdens at surgical margins to guide resections. To address this gap, we developed Ultra-Rapid droplet digital PCR (UR-ddPCR), which can be completed in 15 minutes from tissue to result with an accuracy comparable to standard ddPCR. We demonstrate UR-ddPCR assays for the IDH1 R132H and BRAF V600E clonal mutations that are present in many low-grade gliomas and melanomas, respectively. We illustrate the clinical feasibility of UR-ddPCR by performing it intraoperatively for 13 glioma cases. We further combine UR-ddPCR measurements with UR-stimulated Raman histology intraoperatively to estimate tumor cell densities in addition to tumor cell percentages. We anticipate that UR-ddPCR, along with future refinements in assay instrumentation, will enable novel point-of-care diagnostics and the development of molecularly-guided surgeries that improve clinical outcomes.

Examining cefazolin utilization and perioperative anaphylaxis in patients with and without a penicillin allergy label: A cross-sectional study.

STUDY OBJECTIVE: To compare the occurrence of cefazolin perioperative anaphylaxis (POA) in patients with and without a penicillin allergy label (PAL) to determine whether the prevalence of cefazolin POA differs based on the presence of a PAL. DESIGN: Cross-sectional study. SETTING: A large U.S. healthcare system in the Baltimore-D.C. region, July 2017 to July 2020. PATIENTS: 112,817 surgical encounters across inpatient and outpatient settings in various specialties, involving 90,089 patients. Of these, 4876 (4.3%) encounters had a PAL. INTERVENTIONS: Perioperative cefazolin administration within 4 h before surgery to 4 h after the procedure began. MEASUREMENTS: The primary outcome was cefazolin POA in patients with and without PALs. Potential POA cases were identified based on tryptase orders or diphenhydramine administrations within the initial cefazolin administration to 6 h postoperatively. Verification included two validation steps. The first checked for hypersensitivity reaction (HSR) documentation, and the second, led by Allergy specialists, identified POA and the probable culprit. The secondary outcome looked at cefazolin use trends in patients with a PAL, stratified by setting and specialty. MAIN RESULTS: Of 112,817 encounters, 1421 (1.3%) had possible cefazolin HSRs. Of these, 22 (1.5%) had POA, resulting in a 0.02% prevalence. Of these, 13 (59.1%) were linked to cefazolin and 9 (40.9%) attributed to other drugs. Only one cefazolin POA case had a PAL, indicating no significant difference in cefazolin POA prevalence between patients with and without PALs (p = 0.437). Perioperative cefazolin use in patients with PALs steadily increased from 2.6% to 6.0% between 2017 and 2020, specifically in academic settings. CONCLUSIONS: The prevalence of cefazolin POA does not exhibit significant differences between patients with and without PALs, and notably, the incidence remains remarkably low. Based on these findings, it is advisable to view cefazolin as an acceptable choice for prophylaxis in patients carrying a PAL.

Receptor Tyrosine Kinase EPHA2 Drives Epidermal Differentiation through Regulation of EGFR Signaling.

Intricate signaling systems are required to maintain homeostasis and promote differentiation in the epidermis. Receptor tyrosine kinases are central in orchestrating these systems in epidermal keratinocytes. In particular, EPHA2 and EGFR transduce distinct signals to dictate keratinocyte fate, yet how these cell communication networks are integrated has not been investigated. Our work shows that loss of EPHA2 impairs keratinocyte stratification, differentiation, and barrier function. To determine the mechanism of this dysfunction, we drew from our proteomics data of potential EPHA2 interacting proteins. We identified EGFR as a high-ranking EPHA2 interactor and subsequently validated this interaction. We found that when EPHA2 is reduced, EGFR activation and downstream signaling are intensified and sustained. Evidence indicates that prolonged SRC association contributes to the increase in EGFR signaling. We show that hyperactive EGFR signaling underlies the differentiation defect caused by EPHA2 knockdown because EGFR inhibition restores differentiation in EPHA2-deficient 3-dimensional skin organoids. Our data implicate a mechanism whereby EPHA2 restrains EGFR signaling, allowing for fine tuning in the processes of terminal differentiation and barrier formation. Taken together, we purport that crosstalk between receptor tyrosine kinases EPHA2 and EGFR is critical for epidermal differentiation.

Serial enrichment of heteroduplex DNA using a MutS-magnetic bead system.

Numerous applications in molecular biology and genomics require characterization of mutant DNA molecules present at low levels within a larger sample of non-mutant DNA. This is often achieved either by selectively amplifying mutant DNA, or by sequencing all the DNA followed by computational identification of the mutant DNA. However, selective amplification is challenging for insertions and deletions (indels). Additionally, sequencing all the DNA in a sample may not be cost effective when only the presence of a mutation needs to be ascertained rather than its allelic fraction. The MutS protein evolved to detect DNA heteroduplexes in which the two DNA strands are mismatched. Prior methods have utilized MutS to enrich mutant DNA by hybridizing mutant to non-mutant DNA to create heteroduplexes. However, the purity of heteroduplex DNA these methods achieve is limited because they can only feasibly perform one or two enrichment cycles. We developed a MutS-magnetic bead system that enables rapid serial enrichment cycles. With six cycles, we achieve complete purification of heteroduplex indel DNA originally present at a 5% fraction and over 40-fold enrichment of heteroduplex DNA originally present at a 1% fraction. This system may enable novel approaches for enriching mutant DNA for targeted sequencing.

Single-strand mismatch and damage patterns revealed by single-molecule DNA sequencing.

Mutations accumulate in the genome of every cell of the body throughout life, causing cancer and other genetic diseases1-4. Almost all of these mosaic mutations begin as nucleotide mismatches or damage in only one of the two strands of the DNA prior to becoming double-strand mutations if unrepaired or misrepaired5. However, current DNA sequencing technologies cannot resolve these initial single-strand events. Here, we developed a single-molecule, long-read sequencing method that achieves single-molecule fidelity for single-base substitutions when present in either one or both strands of the DNA. It also detects single-strand cytosine deamination events, a common type of DNA damage. We profiled 110 samples from diverse tissues, including from individuals with cancer-predisposition syndromes, and define the first single-strand mismatch and damage signatures. We find correspondences between these single-strand signatures and known double-strand mutational signatures, which resolves the identity of the initiating lesions. Tumors deficient in both mismatch repair and replicative polymerase proofreading show distinct single-strand mismatch patterns compared to samples deficient in only polymerase proofreading. In the mitochondrial genome, our findings support a mutagenic mechanism occurring primarily during replication. Since the double-strand DNA mutations interrogated by prior studies are only the endpoint of the mutation process, our approach to detect the initiating single-strand events at single-molecule resolution will enable new studies of how mutations arise in a variety of contexts, especially in cancer and aging.

Visual Transformers and Convolutional Neural Networks for Disease Classification on Radiographs: A Comparison of Performance, Sample Efficiency, and Hidden Stratification.

Purpose: To compare performance, sample efficiency, and hidden stratification of visual transformer (ViT) and convolutional neural network (CNN) architectures for diagnosis of disease on chest radiographs and extremity radiographs using transfer learning. Materials and Methods: In this HIPAA-compliant retrospective study, the authors fine-tuned data-efficient image transformers (DeiT) ViT and CNN classification models pretrained on ImageNet using the National Institutes of Health Chest X-ray 14 dataset (112 120 images) and MURA dataset (14 656 images) for thoracic disease and extremity abnormalities, respectively. Performance was assessed on internal test sets and 75 000 external chest radiographs (three datasets). The primary comparison was DeiT-B ViT vs DenseNet121 CNN; secondary comparisons included DeiT-Ti (Tiny), ResNet152, and EfficientNetB7. Sample efficiency was evaluated by training models on varying dataset sizes. Hidden stratification was evaluated by comparing prevalence of chest tubes in pneumothorax false-positive and false-negative predictions and specific abnormalities for MURA false-negative predictions. Results: DeiT-B weighted area under the receiver operating characteristic curve (wAUC) was slightly lower than that for DenseNet121 on chest radiograph (0.78 vs 0.79; P < .001) and extremity (0.887 vs 0.893; P < .001) internal test sets and chest radiograph external test sets (P < .001 for each). DeiT-B and DeiT-Ti both performed slightly worse than all CNNs for chest radiograph and extremity tasks. DeiT-B and DenseNet121 showed similar sample efficiency. DeiT-B had lower chest tube prevalence in false-positive predictions than DenseNet121 (43.1% [324 of 5088] vs 47.9% [2290 of 4782]). Conclusion: Although DeiT models had lower wAUCs than CNNs for chest radiograph and extremity domains, the differences may be negligible in clinical practice. DeiT-B had sample efficiency similar to that of DenseNet121 and may be less susceptible to certain types of hidden stratification.Keywords: Computer-aided Diagnosis, Informatics, Neural Networks, Thorax, Skeletal-Appendicular, Convolutional Neural Network (CNN), Feature Detection, Supervised Learning, Machine Learning, Deep Learning Supplemental material is available for this article. © RSNA, 2022.

Association of Electronic Health Record Use Above Meaningful Use Thresholds With Hospital Quality and Safety Outcomes.

Importance: By 2018, Medicare spent more than $30 billion to incentivize the adoption of electronic health records (EHRs), based partially on the belief that EHRs would improve health care quality and safety. In a time when most hospitals are well past minimum meaningful use (MU) requirements, examining whether EHR implementation beyond the minimum threshold is associated with increased quality and safety may guide the future focus of EHR development and incentive structures. Objective: To determine whether EHR implementation above MU performance thresholds is associated with changes in hospital patient satisfaction, efficiency, and safety. Design, Setting, and Participants: This quantile regression analysis of cross-sectional data used publicly available data sets from 2362 acute care hospitals in the United States participating in both the MU and Hospital Value-Based Purchasing (HVBP) programs from January 1 to December 31, 2016. Data were analyzed from August 1, 2019, to May 22, 2020. Exposures: Seven MU program performance measures, including medication and laboratory orders placed through the EHR, online health information availability and access rates, medication reconciliation through the EHR, patient-specific educational resources, and electronic health information exchange. Main Outcomes and Measures: The HVBP outcomes included patient satisfaction survey dimensions, Medicare spending per beneficiary, and 5 types of hospital-acquired infections. Results: Among the 2362 participating hospitals, mixed associations were found between MU measures and HVBP outcomes, all varying by outcome quantile and in some cases by interaction with EHR vendor. Computerized provider order entry (CPOE) for laboratory orders was associated with decreased ratings of every patient satisfaction outcome at middle quantiles (communication with nurses: ß = -0.33 [P = .04]; communication with physicians: ß = -0.50 [P < .001]; responsiveness of hospital staff: ß = -0.57 [P = .03]; care transition performance: ß = -0.66 [P < .001]; communication about medicines: ß = -0.52 [P = .002]; cleanliness and quietness: ß = -0.58 [P = .007]; discharge information: ß = -0.48 [P < .001]; and overall rating: ß = -0.95 [P < .001]). However, at middle quantiles, CPOE for medication orders was associated with increased ratings for communication with physicians (τ = 0.5; ß = 0.54; P = .009), care transition (τ = 0.5; ß = 1.24; P < .001), discharge information (τ = 0.5; ß = 0.41; P = .01), and overall hospital ratings (τ = 0.5; ß = 0.97; P = .02). At high quantiles, electronic health information exchange was associated with improved ratings of communication with nurses (τ = 0.9; ß = 0.23; P = .03). Medication reconciliation had positive associations with increased communication with nursing at low quantiles (τ = 0.1; ß = 0.60; P < .001), increased discharge information at middle quantiles (τ = 0.5; ß = 0.28; P = .03), and responsiveness of hospital staff at middle (τ = 0.5; ß = 0.77; P = .001) and high (τ = 0.9; ß = 0.84; P = .001) quantiles. Patients accessing their health information online was not associated with any outcomes. Increased use of patient-specific educational resources identified through the EHR was associated with increased ratings of communication with physicians at high quantiles (τ = 0.9; ß = 0.20; P = .02) and with decreased spending at low-spending hospitals (τ = 0.1; ß = -0.40; P = .008). Conclusions and Relevance: Increasing EHR implementation, as measured by MU criteria, was not straightforwardly associated with increased HVBP measures of patient satisfaction, spending, and safety in this study. These results call for a critical evaluation of the criteria by which EHR implementation is measured and increased attention to how different EHR products may lead to differential outcomes.